Computerized virtual paint manufacturing and application system

ABSTRACT

A computer-implemented apparatus and method for coordinating paint-related process steps of at least one paint-related facility. The paint-related process steps exhibit paint-related characteristics. A data acquisition module is provided for acquiring paint characteristic data indicative of the paint-related characteristics. A paint process control data structure is provided for interrelating the acquired paint characteristic data with at least two of the paint-related process steps to produce interrelated paint process control data. A paint process control coordinator is connected to the data acquisition module for storing the acquired paint characteristic data in the paint process control data structure. A data display is connected to the paint process control data structure for remotely receiving and viewing the interrelated paint process control data.

This is a continuation of U.S. patent application Ser. No. 08/966,960,filed Nov. 10, 1997; now U.S. Pat. No. 6,073,055 issued Jun. 6, 2000.

BACKGROUND OF THE INVENTION

1. Field Of The Invention

The present invention relates generally to painting systems and moreparticularly to paint manufacturing, paint application and paint productdata acquisition and processing.

2. Description

Operations within automotive painting contain many devices and processcontrollers that chiefly work independently to achieve their individualgoals. Moreover, data is individually obtained from them without astructured framework to synthesize the data so that an overall systemsanalysis of the painting system can be performed.

Information from automotive painting facilities is not only difficult tosynthesize for an overall systems perspective, but the informationleaves the “hermetic” environment of these painting facilities withgreat difficulty. Outside sources, such as remote customer sites, needaccess to this synthesized information so that they can make informeddecisions about certain operational characteristics of the automotivepainting factories. For instance, customers wish to know how well theirexperimental painting products are performing in the automotive factoryenvironment as well as the paint manufacturers and developers. Alsolacking are the tools needed by the remote sites, to “fine tune”operational parameters in order to fix painting operations orchemistries that are not in tolerance with such predefined standards asMSDS standards. Accordingly, there is a need to overcome these and otherdisadvantages exhibited by previous approaches to operatingpaint-related facilities.

SUMMARY OF THE INVENTION

In accordance with the teachings of the present invention, acomputer-implemented apparatus and method are provided for coordinatingpaint-related process steps of at least one paint-related facility. Thepaint-related process steps exhibit paint-related characteristics. Adata acquisition module is provided for acquiring paint characteristicdata indicative of the paint-related characteristics. A paint processcontrol data structure is provided for interrelating the acquired paintcharacteristic data with at least two of the paint-related process stepsto produce interrelated paint process control data. A paint processcontrol coordinator is connected to the data acquisition module forstoring the acquired paint characteristic data in the paint processcontrol data structure. A data display is connected to the paint processcontrol data structure for remotely receiving and viewing theinterrelated paint process control data.

BRIEF DESCRIPTION OF THE DRAWINGS

Additional advantages and features of the present invention will becomeapparent from the subsequent description in the appended claims, takenin conjunction with the accompanying drawings in which:

FIG. 1 is a process flow diagram depicting the steps involved in theoverall painting system.

FIG. 2 is a network schematic diagram showing the data interconnectionsof the components of the preferred embodiment of the present invention;

FIG. 3 is a network schematic diagram depicting the datainterconnections between a painting laboratory and the virtual paintmanufacturing and application system;

FIG. 4 is a functional data flow diagram depicting the data flow amongcomponents of the present invention;

FIG. 5a is a front view of a painting panel to be analyzed by the paintanalyzer device;

FIG. 5b is an exemplary contour plot output from the paint analyzerdevice that depicts lightness values as related to positions on thepanel of FIG. 5a;

FIGS. 6a-6 b are screen displays of the paint simulator computerprogram;

FIGS. 7a-7 b are schematics of the memory and data structures utilizedwithin the present invention;

FIG. 8 is an exemplary computer screen display for the data acquisitionand interrelationship of resin manufacturing process control data;

FIG. 9 is an exemplary computer screen display for the data acquisitionand interrelationship of paint manufacturing process control data;

FIG. 10 is an exemplary computer screen display for the data acquisitionand interrelationship of vehicle assembly manufacturing process controldata;

FIG. 11a is an exemplary computer screen display showingcross-dependencies through utilization of the links among the datastructures of the present invention;

FIG. 11b is an exemplary computer screen display for the level ofauthorization for accessing the information within the presentinvention;

FIG. 12 is a flow chart depicting the use of the present invention to doenvironmental tolerance checking;

FIG. 13 is a flow chart depicting the steps used in the systemperforming problem resolution and reporting cause and effect analysis;and

FIG. 14 is a flow chart depicting the steps for utilizing the system toform a weekly cause and effect analysis report; and

FIG. 15 is a computer printout depicting an exemplary weekly report asgenerated by the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 1 illustrates the overall steps in a paint manufacturing andapplication system. The ultimate purpose of the overall process is toapply manufactured paint onto a vehicle 50 within predefined tolerances.These tolerances include quality tolerances, and ecological tolerances.

Raw material 54 comes into the paint manufacturing and applicationsystem from an external raw material manufacturing source 62. Moreover,resin 66 comes into the paint manufacturing and application system froman internal raw material manufacturing source 70. The terms “external”and “internal” refer to the sources of the material that internal andexternal to the company that is responsible for the paint manufacturingand delivery of the manufactured paint to a vehicle assembly plant.

Data acquisition is performed with respect to raw material 54 by rawmaterial control process block 74. Likewise, data acquisition concerningresin 66 is performed by resin manufacturing process control block 78.The data acquired by blocks 74 and 78 is specially structured so as toprovide systems-type information with respect to each process stepinvolving raw material 54 and resin 66. Data acquisition is preferablycaptured through electronic sensors that sense the paint-relatedcharacteristics and electronically forward the data to the presentinvention for synthesis and storage. Also, the present inventionsupports manual entry of data as well as electronic retrieving the dataneeded by the present invention directly from databases. This novel dataacquisition and its data structures as utilized by blocks 74 and 78 aremore fully discussed below.

Formulation guidelines 82 indicate the manner by which raw material 54and resin 66 are to be combined in the paint manufacturing process block86 so as to produce paint material 90. These formulation guidelines 82include such guidelines as quantity and temperature at which rawmaterial 54 and resin 66 are to be combined. Data acquisition concerningthe manufacturing of the paint is performed by the paint manufacturingprocess control block 88.

Paint material 90 is delivered to a vehicle assembly plant forprocessing within that plant as indicated by block 94. Within thevehicle assembly plant processing block 94, data acquisition isperformed by assembly plant process control block 98. Block 98 acquiresdata related to paint material 90 and its application as the paintmaterial 90 courses through each process step within vehicle assemblyplant processing block 94. The data as acquired by paint manufacturingprocess control block 88 and assembly plant process control block 98 areused for such purposes as batch control 102. Batch control 102 isintended only for illustration of the use of the present invention andis not intended to limit the scope of application of the presentinvention. Batch control 102 includes analyzing the data acquired fromblocks 88 and 98 to determine whether paint material 90 is withinpredefined tolerances.

The data acquired by blocks 74, 78, 88 and 98 all reside within thecomputerized virtual paint manufacturing and application system 120which structures the data so that an overall system perspective can beobtained as well as by providing an environment for entities to remotelyview the data captured by the present invention.

FIG. 2 shows a network schematic of the interconnections amongcomponents of the computerized virtual paint manufacturing andapplication system 120 and sources of data as generally depicted at 124and recipients of the data as generally depicted at 128. Data sources124 include data being acquired from one or more paint laboratories 132,one or more paint manufacturing factories 136, and one or more vehicleassembly plants 140.

Paint laboratories 132 provide technical data about paint material, suchas mathematical models that interrelate painting factors (e.g., controlsettings for paint spraying equipment) with paint responses (e.g., glossof a paint). The models are stored within the computerized virtual paintmanufacturing and application system 120 in the factor-response modelsdatabase 144. Moreover, paint laboratories 132 provide technical data topopulate one or more of the following data structures that are containedwithin the computerized virtual paint manufacturing and applicationsystem 120: resin manufacturing data structure 148; paint manufacturingdata structure 152; and paint application data structure 156.

The resin manufacturing data structure 148 relates to the data obtainedfrom resin material control process block 74 and resin manufacturingprocess control block 78 (of FIG. 1). Paint manufacturing data structure152 corresponds to the data acquired from paint manufacturing processcontrol block 88 (of FIG. 1). Also, paint application data structure 156corresponds to the data acquired from the assembly plant process controlblock 98 (of FIG. 1).

Data structures 148, 152 and 156 are located on one or more computers asgenerally depicted at 160. The data structures 148, 152, and 156 providea novel structure for assisting in data acquisition from the datasources 124 and in the presentation and analysis of the data by datarecipients 128.

Computers 160 are preferably located within the physical location of thesource of the data. For example, the data that is acquired from paintmanufacturing factory 136 is preferably placed into a computer that islocated at the paint manufacturing factory 136. Likewise, a computercontaining the paint application data structure 156 is located at avehicle assembly plant 140. Data structures 148, 152 and 156 andcomputers 160 are collectively termed the process control coordinator162. Computers 160 have the capability to input and to view data that isstored in databases located on networks 169 subject to computerizedsecurity authorization.

The information as structured by data structures 148, 152, and 156 areable to be retrieved and analyzed by the data recipients 128, such as ata paint manufacturer remote sites 164 and at customer remote sites 168.To allow the data recipients 128 to analyze the painting system from anoverall systems perspective, a technical database 172 providesadditional paint-related data, such as, but not limited to, ecologicaland internal company quality standards.

Networks 169 connect the various components of the system so that datacommunication can occur. The preferred embodiment for networks 169utilizes an Intranet network 173 to perform data communication betweencomponents within the computerized virtual paint manufacturing andapplication system 120 and within the data sources 124. Moreover, paintmanufacturer's remote sites are connected to Intranet 173. The customerremote sites 168 are connected to an Extranet network 175 to betterensure proper security exists in accessing the data from thecomputerized virtual paint manufacturing and application system 120.Security data is located preferably in technical database 172 forensuring that only authorized users (whoever and wherever they may be)can view the portions of the information contained within thecomputerized virtual paint manufacturing and application system 120 thatthey are authorized to view.

FIG. 3 depicts the preferred embodiment for the data interconnectionbetween one of the paint laboratories 132 and the computerized virtualpaint manufacturing and application system 120. Within paint laboratory132, painting equipment 242 is controlled by control settings 244 inorder to spray paint upon vehicles. The sprayed paint is analyzed by apaint analyzer device 246. The paint analyzer device 246 examines thephysical characteristics of the sprayed paint so that subsequentanalysis can reveal how the paint responds under various conditions andunder various formulations. The paint analyzer device 246 examines suchphysical characteristics as, for example, color (e.g., L, a, b values atdifferent angles), leveling (in the form of wave scanned values), gloss,haze, and film thickness. In the preferred embodiment, paint analyzerdevice 246 is a device known as “PROSIM” which is obtainable from BASF.

Paint analyzer device 246 is preferably in data communication with apaint simulation computer program 248. Paint simulation computer program248 models the interrelationship between automotive painting equipmentand the sprayed paint so that desired painting characteristics can beachieved. A factor-response models database 144 is used for storingmathematical models which interrelate painting factors with paintingresponses. Painting factors relate to the control settings 244 of thepainting equipment 242. Painting responses relate to such paintingcharacteristics as those that may be obtained from the paint analyzerdevice 246.

Paint simulation computer program 248 employs design of experimenttechniques, as well as cooptimization techniques in order to determinethe values for the painting responses based upon desired paintingtolerances to be achieved. For a more complete understanding of thepaint simulation computer program 248, please refer to U.S. Pat. No.6,064,919 (entitled “Paint Equipment Set-up Method and Apparatus”),issued May 16, 2000 which is hereby incorporated by reference.

Paint simulation computer program 248 has as one of its purposes thecapability of identifying regions within the mathematical models thatneed to be better defined. For example, a range of painting factorvalues that result in relatively low R-squared values for the paintresponses indicate regions within the mathematical models that needrefinement. These regions within the mathematical models arespecifically tested through a design of experiments technique by thepaint laboratory, and data points are collected by the paint analyzerdevice 246. The design of experiments factor-response models are refinedto incorporate this additional detail.

Computer 160 utilizes paint manufacturing data structure 152 to acquiredata from paint analyzer device 246 and paint simulation computerprogram 248. This acquired data is used for several purposes includingperforming batch control (i.e., to ensure compliance with qualitystandards as contained in the technical database). Such paintcharacteristic data as the paint film thickness data from the paintanalyzer device 246 is interrelated with the type of paint materialwithin the paint manufacturing data structure 152.

Another example is the following. The paint simulation computer program248 performs design of experiments calculations based upon the data fromthe paint analyzer device 246 in order to identify which parameters andvariables are key in the paint manufacturing and vehicle assemblyfactory. These identified key parameters are inserted into the processcontrol data structures (such as the paint manufacturing data structureand the vehicle assembly data structure).

FIG. 4 shows the detailed informational flow among the aforementionedcomponents of the present invention. In the preferred embodiment, thePROSIM device 246 provides paint characteristic data to the paintsimulation computer program 248 so that factor/control settings can bedetermined to produce certain paint appearance and application responsesof the sprayed paint.

The data from the PROSIM device 246 is used by the process controlcoordinator 162 in order to perform batch control. Within that capacity,the PROSIM device 246 allows paint material from a paint manufacturingplant to be analyzed to ensure compliance with predefined qualitystandards. The batch control data from the PROSIM device 246 is used topopulate the paint manufacturing data structure 152 (especially withrespect to the quality forward portion of the data structure).

As described above, paint simulation computer program 248 usesfactor-response models database 144 in order to perform its design ofexperiments calculations. Also, paint simulation computer program 248updates factor-response models database 144 based upon actual paintspraying system performance data as provided by PROSIM device 246. Paintsimulation computer program 248 along with the factor-response modelsdatabase 144 provides the ability to monitor and control variableparameters via technical database 172. Technical database 172, in itspreferred embodiment, contains such information as paint productportfolio information 270, ecology information 272, communicationinformation 274, and quality information 276 (such as first runcapability). Technical database 172 also contains concern and analysisrequest forms 280 so that issues and concerns and their subsequentanalysis and resolution can be captured. Security data 277 about how anentity that is external to the computerized virtual paint manufacturingand application system 120 may access the information is also containedin the technical database 172.

Process control coordinator 162 synthesizes and packages the data fromthe data sources so that remote systems can efficiently and effectivelyanalyze the historical, current and potential operationalcharacteristics of the entire painting system (i.e., life historyanalysis). Process control coordinator 162 synthesizes and packages thedata into the resin manufacturing data structure 148, paintmanufacturing data structure 152, and the paint application datastructure 156 based upon the type of data provided and which particulardata source provided the data.

Additionally, process control coordinator 162 provides problemresolution and reporting information to the data destinations based uponthe information captured by the computerized concern and analysisrequest forms 280. The problem resolution reporting module 282 allowsthe data destination remote sites to use previous solutions to similarproblems in order to solve existing problems. Moreover, a weekly reportmodule 284 of the process control coordinator 162 provides for anautomated capability to send the information from the various componentsof the present invention to the data destination remote sites.

Process control coordinator 246 provides a time stamp for each datumreceived from the data sources. Not only does this create a historicalbaseline snapshot 285, but it also allows the amount of change atdifferent times in the entire paint manufacturing system to be analyzed.

FIG. 5a shows how the PROSIM device captures paint characteristic datafrom panel 290. The regions as exemplarily identified by referencenumeral 291 illustrate where the PROSIM device performs itsmeasurements. For this example, a varying amount of basecoat 292 wasapplied to panel 290. The panel's top 290 a contained a thin coating ofbasecoat whereas the panel's bottom 290 b contained a greater amount ofbasecoat. For this example, a consistent amount of clearcoat 294 wasapplied to panel 290. The varying amount approach with respect tobasecoat 292 is possible with the PROSIM device since the PROSIM devicecaptures paint characteristic data across the entire panel.

To illustrate the entire panel analysis approach of the PROSIM device,FIG. 5b shows a sample contour plot 300 output from the PROSIM devicethat interrelates lightness value of the paint with the position of thepaint on the panel of FIG. 5a. The abscissa axis 302 shows the verticalposition values of the panel while the ordinate axis 304 shows thehorizontal position values of the panel. Regions within contour plot 300reveal how the lightness values vary over panel position. For example,region 306 depicts an area on the panel that has a lightness value asprovided on reference bar 308.

FIG. 6a is an exemplary screen display from the paint simulationcomputer program wherein factor/control settings of the paint sprayingequipment is generally shown at 330. The factor settings areinterrelated through mathematical models with certain responses of thesprayed paint as generally shown at 334 and 338. The mathematical modelswere generated through design of experiments techniques. In thisexample, the bell speed, shaping, and bell fluids factor/controlsettings 330 produce via the mathematical models the paint appearanceand application air response as shown at reference numerals 334 and 338.

With reference to FIG. 6b, a cooptimizer 342 is utilized to maintain oneor more of the factor/control settings and/or response values at acertain level or range while allowing other settings and/or responses tovary within a predefined range. In this example, the shaping air andbell fluids factor/control settings were respectively fixed at 36 poundsper square inch and 295 cubic centimeters/minute. Moreover, in thisexample the average film build response was fixed by the cooptimizer 342to be within the range 0.90 to 1.0 mils. Cooptimizer 342 preferablyemploys a simplex algorithm such as the one provided by the MicrosoftExcel software product.

FIG. 7a depicts the process control data structure template 353 ascontained in the computer memory 360 of computer 160. These componentsare part of the process control coordinator 162.

Process control data structure template 353 interrelates paint-relateddata with one or more relevant process steps of the paint sprayingsystem. The process steps 364 include the steps used within the processof a paint laboratory, or a resin manufacturing factory, or a paintmanufacturing factory, or a vehicle assembly plant. For example, aprocess step within a vehicle assembly plant may include the processstep of when the paint is in storage or when the paint is in the mixingroom, or the particular sprayed paint coating that has been applied to avehicle.

Painting equipment data structure 368 interrelates with relevant processsteps 364 such painting equipment related data as equipment type,accessories, and equipment configuration.

Process data structure 370 interrelates with relevant process steps 364such process-related data as environmental parameters, constantparameters, and variable parameters. Environmental parameters includesuch items as line speed, booth temperature, and humidity. Constantparameters include, but are not limited to, application parameters thatare substantially constant for each paint (e.g., oventemperature/profile, target distance). Variable parameters include, butare not limited to, application parameters that are different for eachpaint (e.g., fluid rate, bell speed).

Materials data structure 372 captures and stores such material relateddata as material parameters, additions to the material mixture, andconsumption data. Specifically, consumption data refers to usageinformation, such as for example, consumption of resources or materialsfor a particular time period (e.g., on a daily basis) or consumption ofresources or materials for a vehicle. Materials data structure 372 ispreferably not interrelated with the process steps since typicallymaterials-related data is not acquired until the end of an entireprocess (such as, at the end of the resin manufacturing process).

Quality forward data structure 373 captures and stores such qualityforward-related data as testing data and evaluation data. The term“quality forward” refers to quality checking for such items as defectsin the material before the material is produced by a painting facility.Quality forward typically uses laboratory testing to formulatepredictions about how a material should perform in production. The paintlaboratory configuration of FIG. 3 is preferably used to formulate suchpredictions for the quality forward data structure 373. Quality forwarddata structure 373 is preferably not interrelated with the process stepssince typically the quality forward-related data is acquired before aprocess for a product begins (such as, at the beginning of the paintmanufacturing process).

With reference to FIG. 7b, quality backward data structure 374 capturesand stores such quality backward related data as first category qualitybackward data, second category quality backward data, and third categoryquality backward data. Quality backward data structure 374 interrelateswith relevant process steps 364 such quality backward-related data astypically three categories of quality backward data. The first categoryaddresses in-process batch control. The second category addressesdefect-kind/type, quantification, and evaluation. The third categoryaddresses: problem description, interim containment actions, potentialcauses(s) identification, root cause identification, verification ofcorrective actions, permanent corrective actions, and preventativeactions. It should be noted that the present invention is not limited tothree categories, but may include only one or two categories dependingon the specification application. For example, the paint applicationdata structure preferably contains only categories two and three for thequality backward related data since typically in-process batch controlis not performed within the paint application process.

The term “quality backward” refers to adjusting the process based uponquality predictions, issues and resolutions identified in the “qualityforward” data structure. In this capacity, “quality backward” operatesas a feedback loop to fine tune the process.

People-related data structure 375 interrelates with relevant processsteps 364 such people-related data as standard training program, jobtitle, and job descriptions.

Painting economic data structure 376 interrelates with relevant processsteps 364 such painting economic data as the money amount per kilogramper gallon of a particular paint type, the amount of money to spray apredefined automotive vehicle, and quality cost that is internal as wellas external.

Lastly, an agreement data structure 384 is provided so as to interrelatecontractual data, such as contract identification number and parties andobligations relevant to an agreement with relevant process steps 364.

Process control coordinator 162 creates and maintains the processcontrol data structure template 353 during the data acquisition stepsfrom each data source.

FIG. 8 depicts the preferred embodiment of the process control datastructure template for the resin manufacturing data structure 148. Theprocess steps which are to be interrelated with the equipment, process,quality backward, people, economy, and agreement modules of the resinmanufacturing data structure 148 are the following: material receipt,material storage, reactor/vessel preparation, intermediate processing,reactor/vessel charging, process, batch adjustment, material transfer,filtration, filling, equipment cleaning, product storage, and productdelivery. It should be understood that the present invention is notlimited to these process steps. The above list serves only for sake ofexample, and can be expanded or reduced based upon the specificapplication at hand.

The primary input materials described by the resin manufacturing datastructure 148 is the chemicals that are used to produce the resins. Thechemicals and their properties are described within the raw materialsmodule of the resin manufacturing data structure 148. The primary outputproduct described by the resin manufacturing data structure 148 are theresins that are produced from the chemicals.

FIG. 9 depicts the preferred embodiment of the process control datastructure template for the paint manufacturing data structure 152. Theprocess steps which are to be interrelated with the equipment, process,quality backward, people, economy, and agreement modules of the paintmanufacturing data structure 152 are the following: material receipt,material storage, staging of materials, equipment preparation, rawmaterial transfer, intermediate processing, batch blending, batchadjustment, filling process, equipment cleaning process, productstorage, and product delivery to the vehicle assembly plant. It shouldbe understood that the present invention is not limited to these processsteps. The above list serves only for sake of example, and can beexpanded or reduced based upon the specific application at hand.

The primary input materials described by the paint manufacturing datastructure 152 are the resins that are the products of the resinmanufacturing data structure 148 and external raw materials (such as,for example, pigments; the external raw materials are shown by referencenumeral 62 on FIG. 1). The resins, the external raw materials, and theproperties associated with them are described within the raw materialsmodule of the paint manufacturing data structure 152. The primary outputproduct described by the paint manufacturing data structure 152 are themanufactured paint materials that are produced from the resins and theexternal raw materials.

FIG. 10 depicts the preferred embodiment of the process control datastructure template for the paint application data structure 156. Theprocess steps which are to be interrelated with the equipment, process,quality backward, people, economy, and agreement modules of the paintapplication data structure 156 are the following: storage-customer,storage-customer mixroom, mixroom, pre-cleaning, phosphate, electrocoat,cleaning-manual, cleaning-automation, manual application,robots-interior/exterior, rotational atomizers-bells, airatomizers-reciprocator, flash-off, blow-off, infrared, ovens,miscellaneous automated applications, manual auxiliary operations,automatic auxiliary operations, zone without application operation,sealant, underbody prime, wax, window glazing, transportation concerns,and coagulation. It should be understood that the present invention isnot limited to these process steps. The above list serves only for sakeof example, and can be expanded or reduced based upon the specificapplication at hand.

The primary input materials described by the paint application datastructure 156 are the paint materials that are the products of the paintmanufacturing data structure 152. The paint materials and theirproperties are described within the materials module of the paintapplication data structure 156. The primary output product described bythe paint application data structure 156 are the paint coatings uponvehicles.

Since variation exists within each painting process (i.e., resinmanufacturing, paint manufacturing and paint application process), datastructures 148, 152, and 156 are structured so that variations andcross-dependencies between materials and process steps can be analyzedwithin each painting process. Moreover, at least one commondenominator/link exists among the data structures 148, 152, and 156 sothat variations and cross-dependencies between materials and processsteps can be analyzed across the entire painting process. Preferably,the link among the data structures 148, 152, and 156 are the outputmaterials from one data structure that corresponds to the input materialto another data structure. For example, the resin material from theresin manufacturing data structure 148 is used to link with informationcontained in the paint manufacturing data structure 152 since the outputof the resin manufacturing data structure 148 corresponds to the inputof the paint manufacturing data structure 152. Numeric identifiers arepreferably used to uniquely identify the materials that link the datastructures. FIG. 11a is a computer screen display that provides anexample of using the links between the data structures to examinecross-dependencies from one paint process to another. In thisnon-limiting example, the problem as identified in the quality backwarddata structure is traced back across materials and processes to thepossible root cause of a wrong quality assurance test being used tocertify that Resin #419 is acceptable for use in production. Moreover,it should be understood that the present invention is not limited toonly linking two data structures but includes linking all three datastructures to form a complete life history view of the entire system,for example, by providing a life history view from the paint applicationdata structure 156 through the paint manufacturing data structure 152 tothe resin manufacturing data structure 148.

FIG. 11b depicts the preferred embodiment to ensure that the data isviewed by data destination remote sites in a secured manner. Forexample, the paint plant area managers which would be identified by acomputer system identifier would only be able to view data within thepresent invention that relates to its own plant.

FIG. 12 depicts the steps wherein the data destination remote sites usesthe information from the various components of the present invention inorder to control the paint spraying system. At process block 400, auser, such as a customer, from a remote site obtains certain technicalinformation regarding the paint spraying system. In order to obtainproduct data sheets, a customer invokes process block 404 by preferablyclicking on an icon on the screen of the data destination remote sitefor a specific paint-related product. The requested product data sheetis retrieved from the technical data base and is sent to the customer atprocess block 408. At process block 412, a customer industrial hygienegroup reviews the product data sheet information and performs at processblock 416 all relevant emissions data. Preferably, the data destinationremote site automatically calculates for the group the emissions dataand produces a report that determines whether the volatile organiccompounds (VOCs) and emissions data are in the specified range asdetermined by the ecological threshold values contained within thetechnical database. This determination is performed by decision block420.

If decision block 420 determines that all VOCs and emissions data are inthe specified range, then the product is determined to be “useful” atprocess block 424. However, if decision block 420 determines that thespecified ranges have been violated, then the data destination remotesite utilizes the paint simulation computer program and the data in thetechnical database in order to return the paint formulation back withinthe specified range. This processing is performed by process block 428.

FIG. 13 depicts the steps for using the present invention in performinga problem resolution and reporting cause and effect analysis. The term“VIS” refers to the information presentation portions of the presentinvention to the data recipients.

At process block 440, a customer detects a problem occurring in acustomer assembly plant. The customer accesses the process controlcoordinator data in order to determine at decision block 448 whether asimilar problem has occurred in the past. If the problem has notoccurred in the past, then the customer initiates at process block 452the concern analysis form that is contained within the technicaldatabase of the present invention. Subsequently, process block 456initiates a resolution procedure and updates the technical database withthe manner in which the concern was addressed and solved. At processblock 460, the customer is able to access the technical database inorder to check on the status of any open PR&Rs (i.e. Problem Resolutionand Reporting).

If decision block 448 has determined that the problem has previouslyoccurred, then the customer at process block 464 identifies the storedcorrective actions taken with respect to that similar problem. Ifcorrective actions are still in place and still being used within thefactory environment as determined by decision block 468, then processblock 452 is executed. However, if past corrective actions are not inplace and not being used, then decision block 472 of the datadestination remote site determines who has responsibility for thecorrective action implementation. Decision block 472 bases thisinformation chiefly upon the agreement data structure of the processcontrol coordinator. If the customer has the responsibility, then atprocess block 476 the customer investigates the failure and reimplementsor changes the corrective action plan. The customer at process block 476uses the information contained within the technical database, as well asthe information from the paint simulation computer program and theprocess control coordinator in order to investigate and correct thefailure. If the factory has the responsibility for the corrective actionas determined by the agreement data structure, then the data destinationremote site notifies factory personnel at process block 480 so that thefactory personnel can investigate the failure and report resolution tothe customer at process block 484.

FIG. 14 shows the steps involved in generating and utilizing automatedweekly reports from the process control coordinator in order to analyzeand control the operational parameters of the paint spraying system. Atprocess block 500, factory technical service representatives input batchspecific data into the process control coordinator data structures inreal time. The batch specific data includes product data, plant data,batch performance data, and defect occurrence and type of defect. Theprocess control coordinator generates a product-specific report thatdetails the activities in the factory using information provided by thetechnical databases and the process control coordinator data structures.

At process block 504, plant personnel access the weekly report from theprocess control coordinator so that at process block 508 the plantpersonnel can use the information to track performance and consistency.This information is used for problem solving and to track defectoccurrence by product. Moreover, the weekly report is automaticallyproduced for customers at process block 512. The customer uses theautomatic weekly report for such operational analyses as: trackingbatches in specific time frames for warranty claims investigation;staying current with plant product and process changes; accessinginformation on trial and experimental products; accessing assembly plantproduct information; tracking factory performance in assembly plant; andviewing assembly plant first run capability weekly by product.

FIG. 15 illustrates a sample weekly report as provided by the presentinvention. Within the weekly report is shown what specifically occurredduring what time frame for a specific paint. Such information can beused to detect problems with respect to a batch for a particular week orover several weeks.

Various other advantages of the present invention will become apparentto those skilled in the art after having the benefit of studying theforegoing text and drawings taken in conjunction with the followingclaims.

What is claimed is:
 1. A computer-implemented apparatus for coordinatingpaint-related process steps of at least one paint-related facility, saidpaint-related process steps exhibiting paint-related characteristics,comprising: a data acquisition module for acquiring paint characteristicdata indicative of the paint-related characteristics; a paint processcontrol data structure for interrelating said acquired paintcharacteristic data with at least two of the paint-related process stepsto produce interrelated paint process control data wherein each one ofthe paint-related process steps occurs at a plurality of paint-relatedfacilities; a paint process control coordinator connected to said dataacquisition module for storing said acquired paint characteristic datain said paint process control data structure; and a data displayconnected to said paint process control data structure for remotelyreceiving and viewing said interrelated paint process control data. 2.The apparatus of claim 1 wherein said process control data structurebeing selected from the group consisting of a resin manufacturing datastructure, a paint manufacturing data structure, paint application datastructure, and combinations thereof.
 3. The apparatus of claim 1 whereinsaid process control data structure includes at least two being selectedfrom the group consisting of an equipment module data structure, aprocess module data structure, a material data structure, a qualityforward data structure, a quality backward data structure, a people datastructure, an economy data structure, an agreement data structure, andcombinations thereof.
 4. The apparatus of claim 3 wherein said processcontrol data structure being selected from the group consisting of aresin manufacturing data structure, a paint manufacturing datastructure, paint application data structure, and combinations thereof.5. The apparatus of claim 4 further comprising: a simplex calculatorconnected to said cooptimizer for constraining said permissible range ofoperational parameters.
 6. The apparatus of claim 1 wherein said processcontrol data structure includes at least one being selected from thegroup consisting of an equipment module data structure, a process moduledata structure, a material data structure, a quality forward datastructure, a quality backward data structure, a people data structure,an economy data structure, an agreement data structure, and combinationsthereof.
 7. The apparatus of claim 1 wherein said paint characteristicdata includes economic data related to the paint-related process steps.8. The apparatus of claim 1 further comprising: paint spraying equipmentfor spraying paint, said sprayed paint exhibiting sprayed paintcharacteristics; a paint analyzer device for generating sprayed paintcharacteristic data based upon analyzing said sprayed paintcharacteristics, said paint process control data structure storing saidsprayed paint characteristic data.
 9. The apparatus of claim 8 furthercomprising: a paint simulator for determining operational parameters foroperating said paint spraying equipment.
 10. The apparatus of claim 9wherein said paint simulator determines said operational parametersbased upon a design of experiments model involving at least one of thesprayed paint characteristics.
 11. The apparatus of claim 9 furthercomprising: a cooptimizer connected to said paint simulator forconstraining the permissible range of said operational parameters ofsaid paint spraying equipment.
 12. The apparatus of claim 1 furthercomprising: a plurality of data displays connected to said paint processcontrol data structure for remotely receiving and viewing saidinterrelated paint process control data.
 13. The apparatus of claim 12further comprising: a security database for providing securityauthorizations with respect to said plurality of data displays forremotely receiving and viewing said interrelated paint process controldata.
 14. A computer-implemented apparatus for coordinatingpaint-related process steps of at least one paint-related facility inorder to spray paint via a paint spraying application process, saidpaint being manufactured from at least two components, saidpaint-related process steps exhibiting paint-related characteristics,comprising: a data acquisition module for acquiring paint characteristicdata indicative of the paint-related characteristics; a paint processcontrol data structure for interrelating said acquired paintcharacteristic data with at least two of the paint-related process stepsto produce interrelated paint process control data, wherein at least oneof the paint-related process steps is related to the paint sprayingapplication process step, wherein at least one of the paint-relatedprocess steps is related to a paint manufacturing process step, saidpaint manufacturing process step being performed prior to the paintspraying application process step and being related to the manufacturingof the paint from the at least two components; a paint process controlcoordinator connected to said data acquisition module for storing saidacquired paint characteristic data in said paint process control datastructure; and a data display connected to said paint process controldata structure for remotely receiving and viewing said interrelatedpaint process control data.